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News Article | May 8, 2017
Site: www.scientificcomputing.com

Product developers talk about time to market. Web service providers measure time to first byte. For James Lowey, the key metric is time to life. Lowey is CIO at the Translational Genomics Research Institute (TGen), a nonprofit focused on turning genomics insights into faster diagnostics and treatments that are more effective. TGen’s genetics research is being applied to rare childhood diseases, cancer, neurological disorders, diabetes and others. “We’ve got patients waiting,” Lowey told the panel audience. “We need to diagnose and treat them. They need results now, not in weeks or months. We’re working to accelerate the movement of insights from the bench to the bedside.” It’s no surprise that each new generation of processors helps organizations like TGen deliver genetic results—and clinical answers—more quickly. Lowey described TGen’s farm of Intel Xeon processor E5 v3 based Dell blade servers based on Intel Scalable System Framework (Intel SSF). Using the blade servers, TGen has reduced processing time for critical genomics processing tasks from two weeks to seven hours, making it fast enough to be clinically relevant. Digital imaging is another area where HPC-enabled speedups are advancing clinical care. Panelist Simon K. Warfield described innovative imaging techniques his team is applying to increase understanding of the brain’s complex circuitry. Dr. Warfield is the Thorne Griscom Professor of Radiology at Harvard Medical School and the founder and director of the Computational Radiology Lab (CRL) at Boston Children's Hospital. CRL is an Intel Parallel Computing Center that is modernizing the algorithms and data structures of medical image computing on Intel Xeon and Intel Xeon Phi processors. The lab is improving cache performance, vectorization performance and multi-threading performance, as well as creating more sophisticated imaging and modeling strategies. CRL can contribute to improved diagnosis and treatment of brain injuries, multiple sclerosis, depression, Alzheimer’s and many other conditions. Consider the novel technique CRL has developed to show more clearly water’s diffusion through the brain—and pinpoint hindrances and restrictions to its flow. In contrast to traditional image processing approaches, CRL’s diffusion-weighted imaging infers new parametric maps from data measurements. Its computational model includes tens or hundreds of 3D images—each up to 10 million pixels each—as its inputs. “This type of analysis is very computationally intensive,” Warfield said. “With the accelerated algorithm and the Intel Xeon Phi processors, we reduced the time needed from 48 hours to 15 minutes of calculations.” That speedup can translate to immediate benefits in for critically ill patients facing brain surgery. That’s because, as Warfield put it, “When you’re talking about surgical planning, life is a matter of time.” Recently, one of the hospital’s neurosurgery teams realized on a Friday that their patient’s conventional magnetic resonance scan was not clear enough to allow them to proceed with a planned brain resection. With the surgery-planning meeting scheduled for Monday, they requested emergency use of CRL’s diffusion imaging algorithm. The patient had a new scan Saturday evening, the data was processed on Sunday, and the information was ready for the team’s decision on Monday. The panel also highlighted precision medicine’s global reach—and its big data challenges. Fang Lin, Director of the Bioinformatics Center at BGI, described BGI’s use of the Lustre file system to help maintain storage performance as its data volumes grow. BGI is a global research leader as well as a provider of genetic testing products. It also operates the China National Genebank, putting it on the forefront of China’s five-year. BGI cranks 20 terabytes of sequencing data every day. The institute stores13petabytes of genomic data and uses a 10 petabyte file system comprising Intel Enterprise Edition for Lustre Software and open source technologies. Dr. David Torrents, a molecular biologist and research professor at the Barcelona Supercomputing Center, shone a spotlight on the importance of collaboration in advancing precision medicine. BSC provides resources to a variety of international centers and consortia. In addition, the institute conducts its own multidisciplinary research in computational biomedicine and related fields. BSC’s alliances also encompass a range of hospitals and medical centers, enabling it to validate and test its models and tools with data from clinical institutions. “We’re at an exciting moment,” Torrents said. “We are not just developing new solutions for personalized medicine, but now are beginning a pilot program in January 2017 to bring them together and apply them in clinical settings, beginning in Catalonia and then throughout Spain.” The panelists say continued leaps forward in precision medicine will come from faster and more sophisticated analysis of larger volumes of more varied data types. “What we want is a more holistic picture, and for that, it’s becoming absolutely critical to combine many diverse data types together for analysis,” said Lowey. To achieve that holistic picture, researchers want to use deep learning and other forms of artificial intelligence. They also want to apply those AI methods to genomic data in combination with imaging data, lifelong clinical records, population studies, environmental studies, and much more. Different aspects of the precision medicine workflow will have varying processing and storage requirements. So the push continues for faster performance with agile or heterogeneous platform architectures rather than a single “silver bullet” approach. The processors will continue as the primary workhorses, supplemented by embedded resources and FPGA accelerators for parts of the workflow. Distributed compute and storage resources will remain crucial, along with advances in applications and tools. As to the clinical impact of these holistic approaches, look no further than Boston Children’s Hospital. Noninvasive prenatal genomic testing can indicate whether a fetus has the risk factors that predispose it to be born with a malformed heart. If genetic testing shows these factors are present, data-intensive digital imaging can reveal whether the heart is actually deformed. By combining genomic with other medical data in this way, clinicians can provide peace of mind for worried parents-to-be, or help them plan for their child’s future. “We’re starting to connect the genetics that predisposes an individual to heart disease, with the imaging to see if the defect is present, and use that information to influence current treatment,” said Warfield. “That information can also help us plan for the child’s longer-term future. We can predict how they’ll do as teenagers and begin to plan accordingly.” Precision medicine is one of the most promising and meaningful applications of high-performance computing today. “It’s still early days, but we’re moving toward an exciting new era of predictive biology and personalized medicine,” said McManus. “Our panelists gave us a great taste of what’s on the horizon. With continued advances in platform technologies, artificial intelligence, and other areas, we create significant opportunities to increase the science of medicine and ultimately improve human health. Intel is excited to empower scientists and clinicians with technology innovations, resources and expertise as we collaborate to make this new era a reality.” Jan Rowell writes about technology trends in HPC, healthcare, life sciences, and other industries.


News Article | May 8, 2017
Site: www.scientificcomputing.com

Product developers talk about time to market. Web service providers measure time to first byte. For James Lowey, the key metric is time to life. Lowey is CIO at the Translational Genomics Research Institute (TGen), a nonprofit focused on turning genomics insights into faster diagnostics and treatments that are more effective. TGen’s genetics research is being applied to rare childhood diseases, cancer, neurological disorders, diabetes and others. “We’ve got patients waiting,” Lowey told the panel audience. “We need to diagnose and treat them. They need results now, not in weeks or months. We’re working to accelerate the movement of insights from the bench to the bedside.” It’s no surprise that each new generation of processors helps organizations like TGen deliver genetic results—and clinical answers—more quickly. Lowey described TGen’s farm of Intel Xeon processor E5 v3 based Dell blade servers based on Intel Scalable System Framework (Intel SSF). Using the blade servers, TGen has reduced processing time for critical genomics processing tasks from two weeks to seven hours, making it fast enough to be clinically relevant. Digital imaging is another area where HPC-enabled speedups are advancing clinical care. Panelist Simon K. Warfield described innovative imaging techniques his team is applying to increase understanding of the brain’s complex circuitry. Dr. Warfield is the Thorne Griscom Professor of Radiology at Harvard Medical School and the founder and director of the Computational Radiology Lab (CRL) at Boston Children's Hospital. CRL is an Intel Parallel Computing Center that is modernizing the algorithms and data structures of medical image computing on Intel Xeon and Intel Xeon Phi processors. The lab is improving cache performance, vectorization performance and multi-threading performance, as well as creating more sophisticated imaging and modeling strategies. CRL can contribute to improved diagnosis and treatment of brain injuries, multiple sclerosis, depression, Alzheimer’s and many other conditions. Consider the novel technique CRL has developed to show more clearly water’s diffusion through the brain—and pinpoint hindrances and restrictions to its flow. In contrast to traditional image processing approaches, CRL’s diffusion-weighted imaging infers new parametric maps from data measurements. Its computational model includes tens or hundreds of 3D images—each up to 10 million pixels each—as its inputs. “This type of analysis is very computationally intensive,” Warfield said. “With the accelerated algorithm and the Intel Xeon Phi processors, we reduced the time needed from 48 hours to 15 minutes of calculations.” That speedup can translate to immediate benefits in for critically ill patients facing brain surgery. That’s because, as Warfield put it, “When you’re talking about surgical planning, life is a matter of time.” Recently, one of the hospital’s neurosurgery teams realized on a Friday that their patient’s conventional magnetic resonance scan was not clear enough to allow them to proceed with a planned brain resection. With the surgery-planning meeting scheduled for Monday, they requested emergency use of CRL’s diffusion imaging algorithm. The patient had a new scan Saturday evening, the data was processed on Sunday, and the information was ready for the team’s decision on Monday. The panel also highlighted precision medicine’s global reach—and its big data challenges. Fang Lin, Director of the Bioinformatics Center at BGI, described BGI’s use of the Lustre file system to help maintain storage performance as its data volumes grow. BGI is a global research leader as well as a provider of genetic testing products. It also operates the China National Genebank, putting it on the forefront of China’s five-year. BGI cranks 20 terabytes of sequencing data every day. The institute stores13petabytes of genomic data and uses a 10 petabyte file system comprising Intel Enterprise Edition for Lustre Software and open source technologies. Dr. David Torrents, a molecular biologist and research professor at the Barcelona Supercomputing Center, shone a spotlight on the importance of collaboration in advancing precision medicine. BSC provides resources to a variety of international centers and consortia. In addition, the institute conducts its own multidisciplinary research in computational biomedicine and related fields. BSC’s alliances also encompass a range of hospitals and medical centers, enabling it to validate and test its models and tools with data from clinical institutions. “We’re at an exciting moment,” Torrents said. “We are not just developing new solutions for personalized medicine, but now are beginning a pilot program in January 2017 to bring them together and apply them in clinical settings, beginning in Catalonia and then throughout Spain.” The panelists say continued leaps forward in precision medicine will come from faster and more sophisticated analysis of larger volumes of more varied data types. “What we want is a more holistic picture, and for that, it’s becoming absolutely critical to combine many diverse data types together for analysis,” said Lowey. To achieve that holistic picture, researchers want to use deep learning and other forms of artificial intelligence. They also want to apply those AI methods to genomic data in combination with imaging data, lifelong clinical records, population studies, environmental studies, and much more. Different aspects of the precision medicine workflow will have varying processing and storage requirements. So the push continues for faster performance with agile or heterogeneous platform architectures rather than a single “silver bullet” approach. The processors will continue as the primary workhorses, supplemented by embedded resources and FPGA accelerators for parts of the workflow. Distributed compute and storage resources will remain crucial, along with advances in applications and tools. As to the clinical impact of these holistic approaches, look no further than Boston Children’s Hospital. Noninvasive prenatal genomic testing can indicate whether a fetus has the risk factors that predispose it to be born with a malformed heart. If genetic testing shows these factors are present, data-intensive digital imaging can reveal whether the heart is actually deformed. By combining genomic with other medical data in this way, clinicians can provide peace of mind for worried parents-to-be, or help them plan for their child’s future. “We’re starting to connect the genetics that predisposes an individual to heart disease, with the imaging to see if the defect is present, and use that information to influence current treatment,” said Warfield. “That information can also help us plan for the child’s longer-term future. We can predict how they’ll do as teenagers and begin to plan accordingly.” Precision medicine is one of the most promising and meaningful applications of high-performance computing today. “It’s still early days, but we’re moving toward an exciting new era of predictive biology and personalized medicine,” said McManus. “Our panelists gave us a great taste of what’s on the horizon. With continued advances in platform technologies, artificial intelligence, and other areas, we create significant opportunities to increase the science of medicine and ultimately improve human health. Intel is excited to empower scientists and clinicians with technology innovations, resources and expertise as we collaborate to make this new era a reality.” Jan Rowell writes about technology trends in HPC, healthcare, life sciences, and other industries.


News Article | May 1, 2017
Site: www.biosciencetechnology.com

Digital imaging is another area where HPC-enabled speedups are advancing clinical care. Panelist Simon K. Warfield described innovative imaging techniques his team is applying to increase understanding of the brain’s complex circuitry. Dr. Warfield is the Thorne Griscom Professor of Radiology at Harvard Medical School and the founder and director of the Computational Radiology Lab (CRL) at Boston Children's Hospital. CRL is an Intel Parallel Computing Center that is modernizing the algorithms and data structures of medical image computing on Intel Xeon and Intel Xeon Phi processors. The lab is improving cache performance, vectorization performance and multi-threading performance, as well as creating more sophisticated imaging and modeling strategies. CRL can contribute to improved diagnosis and treatment of brain injuries, multiple sclerosis, depression, Alzheimer’s and many other conditions. Consider the novel technique CRL has developed to show more clearly water’s diffusion through the brain—and pinpoint hindrances and restrictions to its flow. In contrast to traditional image processing approaches, CRL’s diffusion-weighted imaging infers new parametric maps from data measurements. Its computational model includes tens or hundreds of 3D images—each up to 10 million pixels each—as its inputs. “This type of analysis is very computationally intensive,” Warfield said. “With the accelerated algorithm and the Intel Xeon Phi processors, we reduced the time needed from 48 hours to 15 minutes of calculations.” That speedup can translate to immediate benefits in for critically ill patients facing brain surgery. That’s because, as Warfield put it, “When you’re talking about surgical planning, life is a matter of time.” Recently, one of the hospital’s neurosurgery teams realized on a Friday that their patient’s conventional magnetic resonance scan was not clear enough to allow them to proceed with a planned brain resection. With the surgery-planning meeting scheduled for Monday, they requested emergency use of CRL’s diffusion imaging algorithm. The patient had a new scan Saturday evening, the data was processed on Sunday, and the information was ready for the team’s decision on Monday. The panel also highlighted precision medicine’s global reach—and its big data challenges. Fang Lin, Director of the Bioinformatics Center at BGI, described BGI’s use of the Lustre file system to help maintain storage performance as its data volumes grow. BGI is a global research leader as well as a provider of genetic testing products. It also operates the China National Genebank, putting it on the forefront of China’s five-year. BGI cranks 20 terabytes of sequencing data every day. The institute stores13petabytes of genomic data and uses a 10 petabyte file system comprising Intel Enterprise Edition for Lustre Software and open source technologies. Dr. David Torrents, a molecular biologist and research professor at the Barcelona Supercomputing Center, shone a spotlight on the importance of collaboration in advancing precision medicine. BSC provides resources to a variety of international centers and consortia. In addition, the institute conducts its own multidisciplinary research in computational biomedicine and related fields. BSC’s alliances also encompass a range of hospitals and medical centers, enabling it to validate and test its models and tools with data from clinical institutions. “We’re at an exciting moment,” Torrents said. “We are not just developing new solutions for personalized medicine, but now are beginning a pilot program in January 2017 to bring them together and apply them in clinical settings, beginning in Catalonia and then throughout Spain.” The panelists say continued leaps forward in precision medicine will come from faster and more sophisticated analysis of larger volumes of more varied data types. “What we want is a more holistic picture, and for that, it’s becoming absolutely critical to combine many diverse data types together for analysis,” said Lowey. To achieve that holistic picture, researchers want to use deep learning and other forms of artificial intelligence. They also want to apply those AI methods to genomic data in combination with imaging data, lifelong clinical records, population studies, environmental studies, and much more. Different aspects of the precision medicine workflow will have varying processing and storage requirements. So the push continues for faster performance with agile or heterogeneous platform architectures rather than a single “silver bullet” approach. The processors will continue as the primary workhorses, supplemented by embedded resources and FPGA accelerators for parts of the workflow. Distributed compute and storage resources will remain crucial, along with advances in applications and tools. As to the clinical impact of these holistic approaches, look no further than Boston Children’s Hospital. Noninvasive prenatal genomic testing can indicate whether a fetus has the risk factors that predispose it to be born with a malformed heart. If genetic testing shows these factors are present, data-intensive digital imaging can reveal whether the heart is actually deformed. By combining genomic with other medical data in this way, clinicians can provide peace of mind for worried parents-to-be, or help them plan for their child’s future. “We’re starting to connect the genetics that predisposes an individual to heart disease, with the imaging to see if the defect is present, and use that information to influence current treatment,” said Warfield. “That information can also help us plan for the child’s longer-term future. We can predict how they’ll do as teenagers and begin to plan accordingly.” Precision medicine is one of the most promising and meaningful applications of high-performance computing today. “It’s still early days, but we’re moving toward an exciting new era of predictive biology and personalized medicine,” said McManus. “Our panelists gave us a great taste of what’s on the horizon. With continued advances in platform technologies, artificial intelligence, and other areas, we create significant opportunities to increase the science of medicine and ultimately improve human health. Intel is excited to empower scientists and clinicians with technology innovations, resources and expertise as we collaborate to make this new era a reality.” Jan Rowell writes about technology trends in HPC, healthcare, life sciences, and other industries.


Singh V.,Genopole | Somvanshi P.,Bioinformatics Center
Protein and Peptide Letters | Year: 2010

DNA ligase is an important enzyme and it plays vital role in the replication and repair; also catalyzes nick joining between adjacent bases of DNA. The NAD+ dependent DNA ligase is selectively present in eubacteria and few viruses; but missing in humans. Homology modeling was used to generate 3-D structure of NAD+ dependent DNA ligase (LigA) of Mycobacterium tuberculosis using the known template (PDB: 2OWO). Furthermore, the stereochemical quality and torsion angle of 3-D structure was validated. Numerous effective drugs were selected and the active amino acid residue in LigA was targeted and virtual screening through molecular docking was done. In this analysis, four drugs Chloroquine, Hydroxychloroquine, Putrienscine and Adriamycin were found more potent in inhibition of M. tuberculosis through the robust binding affinity between protein-drug interactions in comparison with the other studied drugs. A phylogenetic tree was constructed and it was observed that homology of LigA in M. tuberculosis resembled with other Mycobacterium species. The conserved active amino acids of LigA may be useful to target these drugs. These findings could be used as the starting point of a rational design of novel antibacterial drugs and its analogs. © 2010 Bentham Science Publishers Ltd.


Jakobsen J.S.,Rigshospitalet | Jakobsen J.S.,The BRIC | Jakobsen J.S.,Danish Stem Cell Center DanStem | Waage J.,Rigshospitalet | And 12 more authors.
Genome Research | Year: 2013

Dynamic shifts in transcription factor binding are central to the regulation of biological processes by allowing rapid changes in gene transcription. However, very few genome-wide studies have examined how transcription factor occupancy is coordinated temporally in vivo in higher animals. Here, we quantified the genome-wide binding patterns of two key hepatocyte transcription factors, CEBPA and CEBPB (also known as C/EBPalpha and C/EBPbeta), at multiple time points during the highly dynamic process of liver regeneration elicited by partial hepatectomy in mouse. Combining these profiles with RNA polymerase II binding data, we find three temporal classes of transcription factor binding to be associated with distinct sets of regulated genes involved in the acute phase response, metabolic/homeostatic functions, or cell cycle progression. Moreover, we demonstrate a previously unrecognized early phase of homeostatic gene expression prior to S-phase entry. By analyzing the three classes of CEBP bound regions, we uncovered mutually exclusive sets of sequence motifs, suggesting temporal codes of CEBP recruitment by differential cobinding with other factors. These findings were validated by sequential ChIP experiments involving a panel of central transcription factors and/or by comparison to external ChIP-seq data. Our quantitative investigation not only provides in vivo evidence for the involvement of many new factors in liver regeneration but also points to similarities in the circuitries regulating self-renewal of differentiated cells. Taken together, our work emphasizes the power of global temporal analyses of transcription factor occupancy to elucidate mechanisms regulating dynamic biological processes in complex higher organisms. © 2013, Published by Cold Spring Harbor Laboratory Press.


Zhang Z.,Fudan University | Wang B.,Bioinformatics Center | Wan B.,Fudan University | Yu L.,Fudan University | Huang Q.,Fudan University
Biochemical and Biophysical Research Communications | Year: 2013

HIV-1 integrase (IN) plays an important role in integrating viral DNA into human genome, which has been considered as the drug target for anti-AIDS therapy. The appearance of drug-resistance mutants urgently requires novel inhibitors that act on non-active site of HIV-1 IN. Nanoparticles have such unique geometrical and chemical properties, which inspires us that nanoparticles like nanotubes may serve as better HIV-1 IN inhibitors than the conventional inhibitors. To test this hypothesis, we performed molecular dynamics (MD) simulation to study the binding of a carbon nanotube (CNT) to a full-length HIV-1 IN. The results showed that the CNT could stably bind to the C-terminal domain (CTD) of HIV-1 IN. The CNT also induced a domain-shift which disrupted the binding channel for viral DNA. Further MD simulation showed that a HIV-1 IN inhibitor, 5ClTEP was successfully sealed inside the uncapped CNT. These results indicate that the CNT may serve as a potential dual-functional HIV-1 IN inhibitor, not only inducing conformation change as an allosteric inhibitor but also carrying small-molecular inhibitors as a drug delivery system. © 2013 Elsevier Inc.


Chitranshi N.,Uttar Pradesh Technical University | Gupta S.,Bioinformatics Center | Tripathi P.K.,Uttar Pradesh Technical University | Seth P.K.,Bioinformatics Center
Medicinal Chemistry Research | Year: 2013

The identification of important chemical features of acetylcholinesterase (AChE) inhibitors will be helpful to discover the potent candidate to inhibit the AChE activity. The best hypothesis from structure-based, Hypo1, one hydrophobic (H) pointed toward ILE444, TRP84, three hydrogen bond accepter (HBA), two hydrogen bond donor, one positive ionizable toward TRP84, PHE330, and 11 excluded volume sphere, were generated using LigandScout. Test and decoy sets were used to corroborate the best hypotheses, and the validated hypotheses were used to screen the Maybridge database. Only 14 compounds were prioritized as promising hits. The quantitative structure-activity relationship (QSAR) equation was developed based on 44 AChE inhibitors: 34 training set compounds and 10 test set compounds. The model was developed using five information-rich descriptors - HBA, log P, HOF, EE, and dipole - playing an important role in determining AChE inhibitory activity. QSAR model (model 3) yielded good statistical data, r 2 = 0.723; q 2 = 0.703; n = 34 for training set. This model was further validated using leave-one-out cross-validation approach, Fischer statistics (F), Y randomisation test, and prediction based on the test data set. Molecular docking of 44 1-indanone derivatives & screened hits compounds were performed to identify the binding residue in AChE. Finally, the screened hits prioritized belong to several classes of molecular scaffolds with several available substitution positions that could allow chemical modification to enhance AChE binding affinity for Alzheimer disease. © 2012 Springer Science+Business Media, LLC.


Daisy P.,Bioinformatics Center | Nivedha R.P.,Bioinformatics Center | Bakiya R.H.,Bioinformatics Center
Asian Journal of Pharmaceutical and Clinical Research | Year: 2013

Tuberculosis is a most dreadful disease causing nearly 2million infection a year. Biotin protein ligase, a key enzyme, which participates in bacterial fatty acid synthesis is indespensible for the existence of Mycobacterium tuberculosis. Targeting biotin protein ligase of Mycobacterium will affect its fatty acid synthesis leads to death of the organism. Molecular docking study on this enzyme was undertaken using ten phyto-ligands from Gloriosa superba. Drug like properties of these ligand were calculated by ADME calculations. Based on the molecular docking results and ADME values Gloriosal was confirmed as a promising lead compound. The present study should therefore play a guiding role in the experimental design and development of Gloriosal as an Antimycobacterial drug.


Zhang L.,CRP Sante | Gu S.,Bioinformatics Center | Liu Y.,Bioinformatics Center | Wang B.,Bioinformatics Center | Azuaje F.,CRP Sante
Bioinformatics | Year: 2012

Summary: Cloud computing offers low cost and highly flexible opportunities in bioinformatics. Its potential has already been demonstrated in high-throughput sequence data analysis. Pathway-based or gene set analysis of expression data has received relatively less attention. We developed a gene set analysis algorithm for biomarker identification in the cloud. The resulting tool, YunBe, is ready to use on Amazon Web Services. Moreover, here we compare its performance to those obtained with desktop and computing cluster solutions. © The Author 2011. Published by Oxford University Press. All rights reserved.


Shipra G.,Bioinformatics Center
Protein and peptide letters | Year: 2012

Bcl-xL protein belongs to BCL-2 family which has either pro- or anti-apoptotic activities owing to their importance in the regulation of apoptosis, tumor genesis and cellular responses to anti-cancer therapy. Bcl-xL permeabilize the outer mitochondrial membrane of cells and inhibit these processes. Protein-inhibitor interactions play an important role in regulating the expression of Bcl-xL protein. Here, we report the docking studies that resulted in the identification of new inhibitors distinct from the previously reported inhibitor against this protein. The results have been validated using Sybyl surflux docking. New potent inhibitors from docking analysis are pentacyclic triterpenoid derivative (2S,4aR,6aR, 6bS,8aS,10R,12R,12aS,12bR,14bR,E)-10,12-dihydroxy-2,4a,14b-trimethyl-9-((((R)-3,4,5-trihydroxy-6-methyl-2H-pyran- 2-yl)oxy)methylene)-1,2,3,4,4a,5,6,6a,6b,8a,9,10,11,12,12a,12b,13,14b-octadecahydropicene-2-car-boxylic acid and 4- alkyl-4-methoxypiperidine derivative 8h (where R= 4-Cl-Ph) that promotes the release of pro-apoptotic proteins from the mitochondria which is a key event in cell death signaling. The compounds form stable complex with protein exhibiting highest binding affinity and Gibbs free energy. Pentacyclic triterpenoid derivatives compound-201 and piperidine derivative compound-39 are potent inhibitors with Ki value of 172.62nM and 175.24 nM high affinity and inhibitory potency. Salt bridge, pi-pi and hydrogen bonding interactions predominantly contribute towards the stability of the complexes. These compounds can further be exploited for their potential to enhance apoptosis. We have established the correlation between the experimental Ki value with our computational inhibition constant. The quantitative predictions in this study provide a scope for further experimental testing giving structural insights into the design and development of novel anticancer drugs.

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