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IC_EX:G16C* AND EN_ALLTXT:(coronavirus OR coronaviruses OR coronaviridae OR coronavirinae OR orthocoronavirus OR orthocoronaviruses OR orthocoronaviridae OR orthocoronavirinae OR betacoronavirus OR betacoronaviruses OR betacoronaviridae OR betacoronavirinae OR sarbecovirus OR sarbecoviruses OR sarbecoviridae OR sarbecovirinae OR "severe acute respiratory syndrome" OR sars OR "2019 ncov" OR covid)

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1 / 35
1.202141019538IN SILICO EVALUATION AND SYNTHESIS OF NOVEL SULFONAMIDES AS PROMISING ANTI-VIRAL LEAD MOLECULES DOCKED AGAINST ANTI-COVID-19 PROTEIN TARGETS: SARS-COV-2 MAIN PROTEASE
IN - 07.05.2021
国際特許分類 (IPC) A61K /
A生活必需品
61医学または獣医学;衛生学
K医薬用,歯科用又は化粧用製剤
 出願番号 202141019538 出願人 SAMPATH CHINNAM 発明者 SAMPATH CHINNAM
COVID-19 pandemic has led us to design and develop novel organic molecules as medicinally promising lead molecules which can prevent the SARS-CoV-2 virus of the infected patients. The current invention provides potential anti-viral drugs docked against anti-COVID-19 protein targets: SARS-CoV-2 main protease, drug-likeness, efficacy, molecular docking, physicochemical and pharmacokinetic studies of novel synthesized sulfonamide analogues. Physicochemical and pharmacokinetic properties have been evaluated on the basis of certain parameters like Lipinski rule of 5 (RO5 rule) and ADMET (absorption, distribution, metabolism, excretion and toxicity). All the synthesized compounds follow Lipinski rule of five (RO5 rule) and the compounds followed the range of rotational bonds, hydrogen bond acceptors (HBA), hydrogen bond donors (HBD), topological surface area (TPSA), and number of violations, etc. All these compounds shown good pharmacokinetic properties, zero renal OCT2 substrate toxicity and negligible toxicity values. BOILED-egg model was carried out for evaluating the gastrointestinal absorption and brain penetration effect. Compounds 3b and 3d comes under white region of egg and exhibited good gastrointestinal absorption, whereas, 3a, 3c, 3e and 3f compounds fall under yellow region (yolk) of egg which showed good brain penetration effect. All novel sulfonamide analogues including commercially available anti-COVID-19 drugs, Hydroxychloroquine and Umifenovir docked with anti-COVID-19 protein targets, i.e., PDB: 6VWW & 6Y2E. Compound 3c when docked with PDB: 6VWW shown maximum energy of -22.06 kcal/mol with two hydrogen binding interactions which are better than marketed drugs. Similarly, compound 3a exhibited highest energy of -14.00 kcal/mol.
2.202111015029DISCOVEY OF BIFENDATE FOR TREATING CORONAVIRIDAE FAMILY OF VIRUS
IN - 17.02.2023
国際特許分類 (IPC) G16C /
G物理学
16特定の用途分野に特に適合した情報通信技術[2018.01]
C計算化学;ケモインフォマティクス;計算材料科学
 出願番号 202111015029 出願人 Sanskriti University 発明者 Dr. Vishal M. Balaramnavar
A method (300) for identifying a binding site of an Ivermectin, the method comprising:developing pharmacophore models to extract features from the Ivermectin;validating the developed pharmacophore models by comparing with pre-defined models of existing coronavirus drugs;performing a ligand-based virtual screening (first virtual screening) of a database of drugs with the validated pharmacophore models; performing a structure-based virtual screening (second virtual screening) of the validated pharmacophore models by structural docking of a target protein into the validated pharmacophore models; assigning a score to each pharmacophore model of the Ivermectin in order to identify the validated pharmacophore models with a high binding affinity and efficiency; and comparing the score obtained from the ligand-based virtual screening (first virtual screening) and the structure-based virtual screening (second virtual screening) for classifying the scored pharmacophore models based on the target protein binding affinity and efficiency for the coronaviridae family of virus.
3.202111015031“DISCOVEY OF IVERMECTIN FOR TREATING CORONAVIRIDAE FAMILY OF VIRUS”
IN - 17.02.2023
国際特許分類 (IPC) G16C /
G物理学
16特定の用途分野に特に適合した情報通信技術[2018.01]
C計算化学;ケモインフォマティクス;計算材料科学
 出願番号 202111015031 出願人 Sanskriti University 発明者 Dr. Vishal M. Balaramnavar
A method (300) for identifying a binding site of an Ivermectin, the method comprising:developing pharmacophore models to extract features from the Ivermectin;validating the developed pharmacophore models by comparing with pre-defined models of existing coronavirus drugs;performing a ligand-based virtual screening (first virtual screening) of a database of drugs with the validated pharmacophore models; performing a structure-based virtual screening (second virtual screening) of the validated pharmacophore models by structural docking of a target protein into the validated pharmacophore models; assigning a score to each pharmacophore model of the Ivermectin in order to identify the validated pharmacophore models with a high binding affinity and efficiency; and comparing the score obtained from the ligand-based virtual screening (first virtual screening) and the structure-based virtual screening (second virtual screening) for classifying the scored pharmacophore models based on the target protein binding affinity and efficiency for the coronaviridae family of virus.
4.202211013566COMPOUNDS INHIBITING PROTEOLYTIC ENZYMES FOR ANTI-SARS-CORONAVIRUS (SARS-COV-2) ACTIVITY
IN - 25.11.2022
国際特許分類 (IPC) C07D /
C化学;冶金
07有機化学
D複素環式化合物(高分子化合物C08)
 出願番号 202211013566 出願人 Chitkara University 発明者 SINGH, Manjinder
The present disclosure relates generally to pharmaceutical compounds. Specifically, the present disclosure provides a compound of Formula I for inhibition of proteolytic enzymes Furin and 3CLpro for anti-SARS-CoV-2 activity or anti-coronavirus activity. The representative compounds exhibited high binding affinity in terms of good docking score and key residue interactions with the proteases. The docked compounds were also noted to have favorable ADME properties and drug-likeness.
5.202111015308“DISCOVEY OF IVERMECTIN FOR TREATING CORONAVIRIDAE FAMILY OF VIRUS”
IN - 17.02.2023
国際特許分類 (IPC) G16C /
G物理学
16特定の用途分野に特に適合した情報通信技術[2018.01]
C計算化学;ケモインフォマティクス;計算材料科学
 出願番号 202111015308 出願人 Sanskriti University 発明者 Dr. Vishal M. Balaramnavar
A method (300) for identifying a binding site of an Ivermectin, the method comprising: developing pharmacophore models to extract features from the Ivermectindrug;validating the developed pharmacophore models by comparing with pre-defined models of existing coronavirus drugs; performing a ligand-based virtual screening (first virtual screening) of a database of drugs with the validated pharmacophore models; performing a structure-based virtual screening (second virtual screening) of the validated pharmacophore models by structural docking of a target protein into the validated pharmacophore models; assigning a score to each pharmacophore model of the Ivermectin in order to identify the validated pharmacophore models with a high binding affinity and efficiency; and comparing the score obtained from the ligand-based virtual screening (first virtual screening) and the structure-based virtual screening (second virtual screening) for classifying the scored pharmacophore models based on the target protein binding affinity and efficiency for the coronaviridae family of virus.
6.202111015161“DISCOVEY OF CEFODIZIME FOR TREATING CORONAVIRIDAE FAMILY OF VIRUS”
IN - 17.02.2023
国際特許分類 (IPC) G16C /
G物理学
16特定の用途分野に特に適合した情報通信技術[2018.01]
C計算化学;ケモインフォマティクス;計算材料科学
 出願番号 202111015161 出願人 Sanskriti University 発明者 Dr. Vishal M. Balaramnavar
A method (300) for identifying a binding site of Cefodizime, the method comprising: developing pharmacophore models to extract features from the Cefodizime; validating the developed pharmacophore models by comparing with pre-defined models of existing coronavirus drugs;performing a ligand-based virtual screening (first virtual screening) of a database of drugs with the validated pharmacophore models; performing a structure-based virtual screening (second virtual screening) of the validated pharmacophore models by structural docking of a target protein into the validated pharmacophore models; assigning a score to each pharmacophore model of the Cefodizime in order to identify the validated pharmacophore models with a high binding affinity and efficiency; and comparing the score obtained from the ligand-based virtual screening (first virtual screening) and the structure-based virtual screening (second virtual screening) for classifying the scored pharmacophore models based on the target protein binding affinity and efficiency for the coronaviridae family of virus.
7.202111015138“DISCOVEY OF DEGARELIX FOR TREATING CORONAVIRIDAE FAMILY OF VIRUS”
IN - 17.02.2023
国際特許分類 (IPC) G16C /
G物理学
16特定の用途分野に特に適合した情報通信技術[2018.01]
C計算化学;ケモインフォマティクス;計算材料科学
 出願番号 202111015138 出願人 Sanskriti University 発明者 Dr. Vishal M. Balaramnavar
A method (300) for identifying a binding site of Degarelix, the method comprising: developing pharmacophore models to extract features from the Degarelix;validating the developed pharmacophore models by comparing with pre¬defined models of existing coronavirus drugs;performing a ligand-based virtual screening (first virtual screening) of a database of drugs with the validated pharmacophore models; performing a structure-based virtual screening (second virtual screening) of the validated pharmacophore models by structural docking of a target protein into the validated pharmacophore models; assigning a score to each pharmacophore model of the Degarelix in order to identify the validated pharmacophore models with a high binding affinity and efficiency; and comparing the score obtained from the ligand-based virtual screening (first virtual screening) and the structure-based virtual screening (second virtual screening) for classifying the scored pharmacophore models based on the target protein binding affinity and efficiency for the coronaviridae family of virus.
8.202111015133“DISCOVEY DEXAMETHASONE FOR TREATING CORONAVIRIDAE FAMILY OF VIRUS”
IN - 17.02.2023
国際特許分類 (IPC) G16C /
G物理学
16特定の用途分野に特に適合した情報通信技術[2018.01]
C計算化学;ケモインフォマティクス;計算材料科学
 出願番号 202111015133 出願人 Sanskriti University 発明者 Dr. Vishal M. Balaramnavar
A method (300) for identifying a binding site of Dexamethasone, the method comprising: developing pharmacophore models to extract features from the Dexamethasone; validating the developed pharmacophore models by comparing with pre-defined models of existing coronavirus drugs; performing a ligand-based virtual screening (first virtual screening) of a database of drugs with the validated pharmacophore models; performing a structure-based virtual screening (second virtual screening) of the validated pharmacophore models by structural docking of a target protein into the validated pharmacophore models; assigning a score to each pharmacophore model of the Dexamethasone in order to identify the validated pharmacophore models with a high binding affinity and efficiency; and comparing the score obtained from the ligand-based virtual screening (first virtual screening) and the structure-based virtual screening (second virtual screening) for classifying the scored pharmacophore models based on the target protein binding affinity and efficiency for the coronaviridae family of virus.
9.202111015462“DISCOVEY OF ENTACAPONE FOR TREATING CORONAVIRIDAE FAMILY OF VIRUS”
IN - 28.01.2022
国際特許分類 (IPC) G16C /
G物理学
16特定の用途分野に特に適合した情報通信技術[2018.01]
C計算化学;ケモインフォマティクス;計算材料科学
 出願番号 202111015462 出願人 Sanskriti University 発明者 Dr. Vishal M. Balaramnavar
A method (300) for identifying a binding site of an Entacapone, the method comprising:developing pharmacophore models to extract features from the Entacapone;validating the developed pharmacophore models by comparing with pre-defined models of existing coronavirus drugs;performing a ligand-based virtual screening (first virtual screening) of a database of drugs with the validated pharmacophore models; performing a structure-based virtual screening (second virtual screening) of the validated pharmacophore models by structural docking of a target protein into the validated pharmacophore models; assigning a score to each pharmacophore model of the Entacapone in order to identify the validated pharmacophore models with a high binding affinity and efficiency; and comparing the score obtained from the ligand-based virtual screening (first virtual screening) and the structure-based virtual screening (second virtual screening) for classifying the scored pharmacophore models based on the target protein binding affinity and efficiency for the coronaviridae family of virus.
10.202111015311“DISCOVEY OF NEFAZODONE FOR TREATING CORONAVIRIDAE FAMILY OF VIRUS”
IN - 17.02.2023
国際特許分類 (IPC) G16C /
G物理学
16特定の用途分野に特に適合した情報通信技術[2018.01]
C計算化学;ケモインフォマティクス;計算材料科学
 出願番号 202111015311 出願人 Sanskriti University 発明者 Dr. Vishal M. Balaramnavar
A method (300) for identifying a binding site of Nefazodone, the method comprising: developing pharmacophore models to extract features from the Nefazodone; validating the developed pharmacophore models by comparing with pre-defined models of existing coronavirus drugs; performing a ligand-based virtual screening (first virtual screening) of a database of drugs with the validated pharmacophore models; performing a structure-based virtual screening (second virtual screening) of the validated pharmacophore models by structural docking of a target protein into the validated pharmacophore models; assigning a score to each pharmacophore model of the Nefazodone in order to identify the validated pharmacophore models with a high binding affinity and efficiency; and comparing the score obtained from the ligand-based virtual screening (first virtual screening) and the structure-based virtual screening (second virtual screening) for classifying the scored pharmacophore models based on the target protein binding affinity and efficiency for the coronaviridae family of virus.
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